A new Secretary Problem is considered, where for fixed k and m one wins if at some time i = m(j .. 1) + 1 up to jm one
selects one of the j best items among the first jm items, j = 1,...,k. Selection is based on relative ranks only.
Interest lies in small k values, such as k = 2 or 3. This is compared with the classical rule, where one wins if one of
the k best among the n = km items is chosen. We prove that the win probability in the new formulation is always larger
than in the classical one. We also show, for k = 2 and 3 that one stops sooner in the new formulation. Numerical
comparisons are included.

Prior research has demonstrated that expressing anger in negotiations is beneficial because it is associated with greater value-claiming. Across four studies, we demonstrate that people interacting with angry counterparts become more likely to walk away from a negotiation, resulting in an impasse. In Study 1, participants who encountered counterparts expressing anger were more likely to reach an impasse, relative to those with neutral counterparts. In Study 2, we adopt an emotion-as-social-information perspective and find that people perceive angry negotiators as being more selfish. In Study 3, we show that the intention to punish mediates the effect of expressed anger on impasses. In Study 4, we demonstrate that the timing of expressing emotions moderates the relationship between expressed anger and impasses. Collectively, our work reveals that expressing anger is risky in negotiations because people are more likely to punish their angry counterparts by walking away from the negotiation table.

Across six studies, I examine the relationship between emotional misrepresentation and trust. I find that emotional misrepresentation, unlike many other types of misrepresentation, can boost trust. Emotional misrepresentation is often perceived to be a signal of self-control and grit. As a result, individuals who misrepresent their emotions to conform to display rules engender higher cognitive trust than individuals who express authentic emotions. Emotional misrepresentation increases cognitive trust across a range of media (face to face interactions, computer-mediated discussions) and across a range of emotions (misrepresented happiness, misrepresented sadness). This research documents the interpersonal benefits of inauthenticity, explores the interplay between organizational display rules and trust, and deepens our understanding of how people react to distinct forms of misrepresentation.

Existing research assumes that deception undermines a person’s trustworthiness and career prospects. Yet, in some occupations, deception persists, and deceptive individuals often advance. The current research unpacks this puzzle by exploring how deception is perceived and enacted across occupations. Integrating research on trust, negotiations, and occupational stereotypes, we predict that deception signals salesmanship, which signals competence and trustworthiness in occupations perceived to rely on salesmanship. As a result, individuals aspiring to join high-salesmanship occupations may actually engage in more deception. Six multi-method, multi-sample studies demonstrate that occupations systematically vary in perceived salesmanship, that deception is seen as more competent and trustworthy in high-salesmanship (e.g., advertising, investment banking) than low-salesmanship occupations (e.g., accounting, non-profit), and that deception therefore emerges more frequently in high-salesmanship occupations. In addition to suggesting interventions that could curb deception, these results extend theory in several ways, particularly by documenting occupational variation in the foundations of trust.

When is lying ethical? Through a large inductive study, and a series of experiments, I develop and test a descriptive moral theory to shed light on this fundamental question. Deception is perceived to be ethical when honesty causes unnecessary harm. Perceptions of “unnecessary harm” are influenced by two key dimensions: the degree to which honesty will harm an individual at the moment of communication, and the instrumental value of truth, which is a factor of the meaningfulness, use, and objectivity of the honest information. Perceptions of unnecessary harm dictate nine implicit rules – pertaining to the targets, topics, and timing of a conversation – that specify the systematic circumstances in which deception is perceived to be ethical. I demonstrate that unnecessary harm is a key driver of moral judgments of deception and I rule out a series of alternative theories that have been proposed in philosophy and moral psychology. This research provides insight into when and why people value honesty, and paves the way for future research on when and why people embrace deception.

Trust is critical for our cooperation and effective working relationships, but trust also enables exploitation and unethical behavior. Prior trust research has disproportionately focused on the benefits of trust, even though some of the most egregious unethical behaviors occur because of misplaced trust. Targets of exploitation often overweight the wrong trust cues and are exploited by people who either opportunistically or strategically take advantage of trusting targets. We call for future work to explore the critical link between trust and unethical behavior.

We consider the problem of modeling and optimally selecting a portfolio of loans which are subject to default and/or prepayment risk. Examples include mortgage- and asset-backed securities (e.g., credit cards and student, auto, and commercial loans) and portfolios of business loans. The size of these portfolios can range from the thousands to millions, with each loan being characterized by high-dimensional loan-level data. The optimization problem is a high-dimensional nonlinear integer program which typically breaks down with scale. We instead propose an approximate optimization approach which yields an asymptotically optimal portfolio. The asymptotic portfolio becomes more exact as the scale of the problem increases, converging to the optimal portfolio as its size grows large. Using actual mortgage data, we demonstrate the efficiency of the approximate optimization approach which is typically many orders of magnitude faster than nonlinear integer program solvers while also being highly accurate even for moderately-sized portfolios.

People often brag about, or advertise, their good deeds to others. Seven studies investigate how bragging about prosocial behavior affects perceived generosity. The authors propose that bragging conveys information about an actor’s good deeds, leading to an attribution of generosity. However, bragging also signals a selfish motivation (a desire for credit) that undermines the attribution of generosity. Thus, bragging has a positive effect when prosocial behavior is unknown because it informs others that an actor has behaved generously. However, bragging does not help—and often hurts—when prosocial behavior is already known, because it signals a selfish motive. Additionally, the authors demonstrate that conspicuous cause marketing products have effects akin to bragging by signaling an impure motive for doing good deeds. Finally, the authors argue that bragging about prosocial behavior is unique because it undermines the precise information that the braggart is trying to convey (generosity). In contrast, bragging about personal achievements does not affect perceptions of the focal trait conveyed in the brag. These findings underscore the strategic considerations inherent in signaling altruism.

Credem, an Italian regional bank, grants loans to Parmigiano Reggiano producers and holds the cheese as collateral in its own warehouse during the maturation process, essentially replacing part of the operations for the cheese producers and gaining deep operations expertise.

The incidence of obesity in the United States has tripled over the past fifty years, posing significant challenges for organizations. We build on stereotype content research and offer an overarching framework to understand individuals’ affective, cognitive, and behavioral responses to obesity. Across five studies, we demonstrate that individuals associate obesity with perceptions of low competence. Perceptions of low competence predict affective (disgust, sympathy) and behavioral (low help, high harm) responses to obesity. Consistent with the BIAS Map (Cuddy, Fiske, & Glick, 2007), these discriminatory responses are moderated by perceptions of warmth. We demonstrate that, in some cases, shifting perceptions of warmth is just as effective as losing weight for curtailing discrimination towards the obese. Our findings demonstrate that social categorization is labile and we offer prescriptive advice for individuals seeking to change the way others perceive them.

Philosophers, psychologists, and economists have long asserted that deception harms trust. We challenge this claim. Across four studies, we demonstrate that deception can increase trust. Specifically, prosocial lies increase the willingness to pass money in the trust game, a behavioral measure of benevolence-based trust. In Studies 1a and 1b, we find that altruistic lies increase trust when deception is directly experienced and when it is merely observed. In Study 2, we demonstrate that mutually beneficial lies also increase trust. In Study 3, we disentangle the effects of intentions and deception; intentions are far more important than deception for building benevolence-based trust. In Study 4, we examine how prosocial lies influence integrity-based trust. We introduce a new economic game, the Rely-or-Verify game, to measure integrity-based trust. Prosocial lies increase benevolence-based trust, but harm integrity-based trust. Our findings expand our understanding of deception and deepen our insight into the mechanics of trust.

There has been significant recent interest in studying consumer behavior in sponsored search advertising (SSA). Researchers have typically used daily data from search engines containing measures such as average bid, average ad position, total impressions, clicks and cost for each keyword in the advertiser's campaign. A variety of random utility models have been estimated using such data and the results have helped researchers explore the factors that drive consumer click and conversion propensities. However, virtually every analysis of this kind has ignored the intra-day variation in ad position. We show that estimating random utility models on aggregated (daily) data without accounting for this variation will lead to systematically biased estimates -- specifically, the impact of ad position on click-through rate (CTR) is attenuated and the predicted CTR is higher than the actual CTR. We demonstrate the existence of the bias analytically and show the effect of the bias on the equilibrium of the SSA auction. Using a large dataset from a major search engine, we measure the magnitude of bias and quantify the losses suffered by the search engine and an advertiser using aggregate data. The search engine revenue loss can be as high as 11% due to aggregation bias. We also present a few data summarization techniques that can be used by search engines to reduce or eliminate the bias.